Predictors of Atrial Fibrillation Late Recurrence and Major Adverse Cardiovascular Events After Radiofrequency Catheter Ablation: A Clinical Nomogram Model

Yan-Xiang Zhou, Yu-Gang Hu, Sheng Cao, Jia-Rui Lei, Fen-Fen Xu, Tuan-Tuan Tan, Qing Zhou Department of Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of ChinaCorrespondence: Qing Zhou, Department of Ultrasonography, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, Hubei, 430060, People’s Republic of China, Tel + 86 027 88041911 x88037, Fax +86 027 88040334, Email [email protected]: This study sought to investigate the predictive factors for atrial fibrillation late recurrence (AFLR) and major adverse cardiovascular events (MACEs) in atrial fibrillation (AF) patients after radiofrequency catheter ablation (RFCA) and construct a nomogram prediction model for providing precious information of screening the high risk patients and giving appropriate preventive interventions.Patients and Methods: A total of 128 patients with atrial fibrillation (AF) who underwent RFCA were enrolled. Univariate and multivariate Cox regression were used to screen the predictors of AFLR and MACEs (including rehospitalization due to AF recurrence, heart failure, myocardial infarction, coronary revascularization, stroke and all-cause mortality). The nomogram model was constructed to predict AFLR after RFCA. Risk stratification based on the nomogram further predicted AFLR and MACEs after RFCA. Subgroup analysis and survival analysis of high and low risk groups in individuals with AF after RFCA were performed.Results: During median follow-up of 76.50 (5.75) months, 71 (55.47%) patients experienced AFLR, while 56 (43.75%) suffered from MACEs. Early recurrence, maximum left atrial volume index (LAVImax) and E/Vp were the independent risk factors for predicting AFLR after RFCA. And AFLR was the only independent predictor for MACEs. Accordingly, a nomogram prediction model based on early recurrence, LAVImax and E/Vp was constructed, the 1-year, 3-year and 5-year AUC of AFLR were 0.904, 0.826 and 0.793, respectively. Risk stratification based on the nomogram had high predictive value for AFLR and MACEs. The Kaplan–Meier survival curves showed great discrimination between the low and high risk groups in the probability of free from AFLR and MACEs.Conclusion: The nomogram model based on early recurrence, LAVImax and E/Vp can be used to predict the AFLR and MACEs after RFCA accurately and individually, in order to provide scientific and effective patient management basis for AF patients after RFCA.Keywords: atrial fibrillation, radiofrequency catheter ablation, late recurrence, major adverse cardiovascular events

Authors

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2026-01-01
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictors of Atrial Fibrillation Late Recurrence and Major Adverse Cardiovascular Events After Radiofrequency Catheter Ablation: A Clinical Nomogram Model

Tan TT, Lei JR, Hu YG, Cao S et al.
SHILAP Revista de lepidopterología
Atrial Fibrillation Management and Outcomes
article

Predictors of Atrial Fibrillation Late Recurrence and Major Adverse Cardiovascular Events After Radiofrequency Catheter Ablation: A Clinical Nomogram Model

Tan TT, Lei JR, Hu YG, Cao S, Zhou Q, Xu FF, Zhou YX
article en

Abstract

Yan-Xiang Zhou, Yu-Gang Hu, Sheng Cao, Jia-Rui Lei, Fen-Fen Xu, Tuan-Tuan Tan, Qing Zhou Department of Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of ChinaCorrespondence: Qing Zhou, Department of Ultrasonography, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, Hubei, 430060, People’s Republic of China, Tel + 86 027 88041911 x88037, Fax +86 027 88040334, Email [email protected]: This study sought to investigate the predictive factors for atrial fibrillation late recurrence (AFLR) and major adverse cardiovascular events (MACEs) in atrial fibrillation (AF) patients after radiofrequency catheter ablation (RFCA) and construct a nomogram prediction model for providing precious information of screening the high risk patients and giving appropriate preventive interventions.Patients and Methods: A total of 128 patients with atrial fibrillation (AF) who underwent RFCA were enrolled. Univariate and multivariate Cox regression were used to screen the predictors of AFLR and MACEs (including rehospitalization due to AF recurrence, heart failure, myocardial infarction, coronary revascularization, stroke and all-cause mortality). The nomogram model was constructed to predict AFLR after RFCA. Risk stratification based on the nomogram further predicted AFLR and MACEs after RFCA. Subgroup analysis and survival analysis of high and low risk groups in individuals with AF after RFCA were performed.Results: During median follow-up of 76.50 (5.75) months, 71 (55.47%) patients experienced AFLR, while 56 (43.75%) suffered from MACEs. Early recurrence, maximum left atrial volume index (LAVImax) and E/Vp were the independent risk factors for predicting AFLR after RFCA. And AFLR was the only independent predictor for MACEs. Accordingly, a nomogram prediction model based on early recurrence, LAVImax and E/Vp was constructed, the 1-year, 3-year and 5-year AUC of AFLR were 0.904, 0.826 and 0.793, respectively. Risk stratification based on the nomogram had high predictive value for AFLR and MACEs. The Kaplan–Meier survival curves showed great discrimination between the low and high risk groups in the probability of free from AFLR and MACEs.Conclusion: The nomogram model based on early recurrence, LAVImax and E/Vp can be used to predict the AFLR and MACEs after RFCA accurately and individually, in order to provide scientific and effective patient management basis for AF patients after RFCA.Keywords: atrial fibrillation, radiofrequency catheter ablation, late recurrence, major adverse cardiovascular events

SHILAP Revista de lepidopterología
Good health and well-being
Openalex Percentile: Top 93%
Atrial Fibrillation Management and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.